The Government of India has taken another significant step toward strengthening its artificial intelligence capabilities by releasing a policy white paper that outlines a roadmap for building indigenous AI foundation models.
The document, issued by the Office of the Principal Scientific Adviser to the Government of India, emphasizes the importance of developing homegrown AI technologies that align with India’s socio-economic priorities, legal framework, and national security requirements.
Titled “Advancing Indigenous Foundation Models”, the white paper is part of an ongoing AI Policy White Paper Series aimed at shaping India’s long-term artificial intelligence strategy. The initiative reflects the government’s broader vision to position the country as a global hub for responsible and inclusive AI development.
The newly released document lays out a strategic framework for developing AI systems designed specifically for India’s linguistic, cultural, and economic diversity. According to the report, indigenous foundation models are essential to ensure that artificial intelligence technologies benefit the country’s population while remaining aligned with national priorities.
The report states that developing domestic AI infrastructure can help ensure inclusive growth, improve public services, and enhance India’s role in the global AI ecosystem.
Such models could also support government initiatives aimed at strengthening digital governance and improving access to technology in underserved communities.
Foundation models are large-scale artificial intelligence systems trained on vast datasets that include text, images, audio, and video. These models serve as a foundational layer for numerous AI applications.
They are capable of performing a wide range of tasks, including:
Language translation
Text summarisation
Question answering
Text classification
Image and multimedia analysis
Because of their versatility, foundation models have become a core building block of modern AI ecosystems worldwide.
According to the white paper, India aims to create foundation models trained on datasets relevant to the country’s unique linguistic and cultural diversity. Such an approach can improve the accuracy and fairness of AI applications deployed within India.
Currently, many AI tools used in the country are developed abroad and trained primarily on global datasets that may not fully represent Indian languages, contexts, or social realities.
Developing domestic models could help address these limitations while ensuring that AI technologies are more inclusive and responsive to India’s needs.
The white paper highlights the importance of both Large Language Models (LLMs) and Small Language Models (SLMs) in building a robust AI ecosystem.
LLMs are large-scale AI models designed to handle a wide range of tasks across industries. They are capable of performing complex language-related functions and can support applications in research, customer service, digital assistants, and knowledge management.
SLMs, on the other hand, are smaller and specialised AI systems that focus on specific domains. These models typically require less computing power and are more cost-efficient to deploy.
In India, SLMs could play a significant role in sectors such as:
Agriculture advisory systems
Healthcare diagnostics and telemedicine
Education and digital learning platforms
Micro, small and medium enterprises (MSMEs)
The integration of LLMs, SLMs, and multimodal AI models could help:
Promote linguistic inclusivity across India’s many languages
Reduce costs associated with AI deployment
Improve energy efficiency in computing infrastructure
Such technologies could also drive innovation in several key sectors, including:
Climate monitoring and sustainability initiatives
Public health and medical research
Education technology and digital classrooms
Urban planning and governance systems
To accelerate the development of indigenous AI systems, the government is encouraging collaboration between public institutions, academic researchers, and private technology companies.
This cooperative approach is expected to help build a strong ecosystem capable of developing scalable AI infrastructure and innovative digital solutions.
India has already launched initiatives such as the IndiaAI Mission, which focuses on building computing infrastructure, promoting AI startups, and supporting research in emerging technologies.
Artificial intelligence is increasingly being viewed as a strategic technology that will shape economic growth, global competitiveness, and national security.
By prioritising indigenous AI development, India aims to:
Reduce dependence on foreign AI systems
Strengthen data sovereignty
Encourage domestic innovation
Ensure responsible and ethical AI deployment
Such efforts are also aligned with the government’s broader digital transformation initiatives aimed at expanding digital services and strengthening technology infrastructure across the country.
The release of the white paper on indigenous foundation models marks an important milestone in India’s journey toward becoming a global leader in artificial intelligence. By focusing on locally trained AI systems that reflect the country’s linguistic diversity and societal needs, India aims to create a more inclusive and resilient digital ecosystem.
Through collaboration between government, academia, and industry, the development of LLMs, SLMs, and multimodal AI models could significantly expand the role of AI in sectors such as healthcare, agriculture, education, and governance. As global competition in artificial intelligence intensifies, building indigenous AI capabilities will be critical for ensuring technological sovereignty, innovation, and sustainable economic growth.